Engineering Development Process Research Articles

A Framework for the Construction and Tailoring of Engineering Development Process Models

A well-balanced project design using appropriate process models is an important success factor for the management of engineering development projects. There exists a wide range of different process models, including traditional waterfall-based models as well as agile development models like Scrum. Such standardized process models offer a good starting point for the management of engineering development projects; however, they have to be tailored in order to meet the needs of a specific project. Additionally, in complex environments, it might be necessary to construct dedicated process models, like hybrid combinations of several models. In this article, the groundwork for a systematic approach to the construction and tailoring of process models for engineering development projects is presented. It considers relevant international standards as well as traditional and agile process models and can serve as a basis for the subsequent tailoring processes. The developed framework offers the possibility to add distinctive characteristics to a process model, like means which facilitate quality, communication, or knowledge transfer. The evaluation of the framework was done by means of a case study, a survey, and expert interviews.

Study on the Design Stage from a Dimensional and Energetic Point of View for a Marine Technical Water Generator Suitable for a Medium Size Container Ship

The purpose of this study is to provide an overview of the development of the modern low-speed marine two-stroke diesel engine from the point of view of the technical water cooling plant, taking into account and starting from the market requirements for power and speed, with information and design options relevant to the entire shipping industry. Thus, through the ideas of this project, we analyze notions and relevant aspects of systems related to marine slow turning engines, including the basic thermodynamic structure of the technical water system designed for a marine engine. This study also presents the design criteria that define the size and design concept of the engine structure components, with a focus on the technical water cooling installation. The concepts for the main engine hot parts served by the technical water cooling installation play a vital role in the marine technical water generator. The choices the engine designer must make regarding basic auxiliary systems, such as fuel injection and exhaust valve actuation, are important factors to keep in mind when installing a technical water generator onboard a ship. The automation and control systems that govern the modern electronic engine, which drive the supply pump of the technical water cooling system can provide a simplified view of the engine development process. In order to point out the contributions of this study, it is important to focus on the calculations used to determine the main parameters of a technical water generator especially designed for a midsized container ship.

Integration of Core First Year Engineering Courses into Sequenced Experiential Learning: The Integrated Cornerstone

Until the beginning of the 2020 academic year, the first-year engineering program at McMaster University was organized as traditional courses to form a common curriculum for all students. The first year core courses were organized as i) Design and Graphics, ii) Computation, iii) Profession & Practice, and iv) Materials. Regardless of which engineering discipline a student enters in second year, the core courses provide a common base for important theory and applications required for the engineering design and development process. The challenge with traditional course organization continues to be concept linkages and attention competition. The purpose of this new approach was to integrate the learning objective of each traditional course into one experiential course through sequential Capstone-style project learning experiences– creating the Integrated Cornerstone. As the name implies, the approach offers the foundational blocks in the engineering student’s education. Focusing pedagogy on a tangible outcomes provides the opportunity to incorporate creativity, self-efficacy, and fosters a sense of community. The Achilles’ heel to a siloed collection of courses offering the Cornerstone approach is that students find themselves immersed in parallel independent projects resulting in unintended distraction. The Integrated Cornerstone merges the core courses learning objectives for better focus of pedagogy. While pandemic restrictions have complicated the quantified comparison of pedagogical approaches between the traditional method of curriculum delivery vs. the Integrated Cornerstone delivery we present aggregate qualitative outcomes of student success. The comparison of approaches and lessons learned for integration will be of interest to other educators seeking better integrated learning for the application of engineering theory in design.

Conditioning of simulated cesium radionuclides in NaOH-activated fly ash-based geopolymers

The growing nuclear safety concerns call for better solutions than traditional Portland cement-based materials to retain radionuclides especially Cesium (Cs). This work explored engineering process development and characterization of low-cost sustainable NaOH-activated fly ash-based geopolymers (FA-GP) as a conditioning matrix for non-radioactive equivalent of Cs (133Cs+). The effects of processing parameters on the FA-GP microstructure, porosity, in-situ zeolite crystallization, and Cs immobilization performance (quantified as the Leachability Index LX) were investigated and compared with literature data. The immobilization of non-radioactive equivalent of Cs (133Cs+) in NaOH-activated FA-GP was investigated using factorial design of experiments. The Cs leachability index (LX) was evaluated according to ANSI/ANS-16.1. FA-GP were characterized using SEM, XRD, and N2 adsorption-desorption isotherms. The results revealed that the main factors influencing Cs immobilization were the curing temperature and the interaction between Cs dosage and curing temperature. LX ≥12 and effective diffusion coefficient De ≤10−12 cm2/s was obtained for FA-GP cured at 90 °C. The effective diffusivity was about 5–7 orders of magnitude lower than for the conventional Portland cement-based encapsulation materials. Enhanced immobilization of Cs (LX = 14.6, De = 2.5 × 10−15 cm2/s), not reported hitherto, was further achieved by in-situ pollucite (Cs,Na)2Al2Si4O12.2H2O crystallization within FA-GP via one-step synthesis route at 90 °C. In addition, leaching studies on powdered FA-GP demonstrated encouraging performance and reliability of FA-GP under extreme mechanical conditions. It therefore appears that FA-GP could be a promising nuclear waste immobilization material, especially for the waste containing high concentration of Cs.

Ultra-low NOx diesel aftertreatment: An assessment by simulation

Upcoming Euro 7/VII regulations are under discussion, and, from available information, they will focus not only on reducing the current emission limits but also on all those operating conditions that are still responsible for high emission events (e. g. cold start or altitude) as well as regulating secondary emissions with a major focus on GHGs (N2O, CH4 and HCHO). In this perspective, robustness towards a broader range of operative and environmental conditions and high conversion efficiency against all pollutants species will be demanded to aftertreatment systems.In an engine development process, the activity of aftertreatment architecture selection requires huge efforts in terms of time, hardware procurement, facilities and resources. That is because different topological layouts, different technologies and different interactions between the engine and the After-Treament System (ATS) must be investigated to find the most suitable solution. In this perspective, virtual testing is a strong and precious tool to accelerate and substantially reduce development effort with respect to an experimental campaign.The present work aims at showing a deep dive into an aftertreatment modeling and simulation approach in which experimental data coming from steady state and dynamic characterizations are used at first to calibrate 1D catalyst kinetic models and in a second step as input to homologation cycles for ATS performance evaluations. Modeling, validation and an example of aftertreatment technology and layout screening in the context of Euro 7 future scenario proposed by CLOVE will be discussed as well, to clarify how a technology emission reduction walk could be built with such an approach.

Effect of biomethane substitution on combustion noise and performance of a dual fuel common rail direct injection diesel engine

AbstractRising pollution levels and stringent emission regulations have raised the requirement for the utilization of alternative green fuels as a sustainable energy source for engine applications. The economic and environmental benefits of using biomethane or renewable natural gas (>95% methane) in diesel engines have made it a promising solution. Sound levels caused by combustion noise, however, is an area of concern in the early stages of engine development process, and to the best of our knowledge studies related to the impact of gaseous fuel energy share on combustion noise in dual fuel diesel engines have not been reported in the literature. In the present work, experimental research on the combustion noise of a biomethane augmented dual fuel common‐rail direct injection (CRDI) diesel engine has been carried out with a correlational design of its performance and combustion characteristics at various engine operating conditions. Comparative results on combustion and performance characteristics of different fuel compositions at various engine loads revealed that there is a better utilization of gaseous fuel at full load conditions resulting in improved power output and reduced heat transfer losses. Cylinder pressure spectra derived from recorded in‐cylinder pressure were used for carrying out the quantitative analysis of sound levels. The results suggested that an increment in methane share is effective in controlling the sound pressure levels to 95 dB (at 1.5 Newton‐meter [Nm] and 13.5 Nm loading conditions) and it is lower than the diesel‐only operational levels at all loading conditions.

A Cyber-Physical Prototyping and Testing Framework to Enable the Rapid Development of UAVs

In this work, a cyber-physical prototyping and testing framework to enable the rapid development of UAVs is conceived and demonstrated. The UAV Development Framework is an extension of the typical iterative engineering design and development process, specifically applied to the rapid development of UAVs. Unlike other development frameworks in the literature, the presented framework allows for iteration throughout the entire development process from design to construction, using a mixture of simulated and real-life testing as well as cross-aircraft development. The framework presented includes low- and high-order methods and tools that can be applied to a broad range of fixed-wing UAVs and can either be combined and executed simultaneously or be executed sequentially. As part of this work, seven novel and enhanced methods and tools were developed that apply to fixed-wing UAVs in the areas of: flight testing, measurement, modeling and emulation, and optimization. A demonstration of the framework to quickly develop an unmanned aircraft for agricultural field surveillance is presented.

Aeroelastic Stability of Combined Plunge-Pitch Mode Shapes in a Linear Compressor Cascade

Modern aeroengine designs strive for peak specific fuel and thermal efficiency. To achieve these goals, engines have more highly loaded compressor stages, thinner aerofoils, and blended titanium integrated disks (blisks) to reduce weight. These configurations promote the occurrence of aeroelastic phenomena such as flutter. Two important parameters known to influence flutter stability are the reduced frequency and the ratio of plunge and pitch components in a combined flap mode shape. These are used as design criteria in the engine development process. However, the limit of these criteria is not fully understood. The following research aims to bridge the gap between semi-analytical models and modern compressors by systematically investigating the flutter stability of a linear compressor cascade. This paper introduces the plunge-to-pitch incidence ratio, which is defined as a function of reduced frequency and pitch axis setback for a first flap (1F) mode shape. Using numerical simulations, in addition to experimental validation, aerodynamic damping is computed for many modes to build stability maps. The results confirm the importance of these two parameters in compressor aeroelastic stability as well as demonstrate the significance of the plunge-to-pitch incidence ratio for predicting the flutter limit.

Graph Rewriting Techniques in Engineering Design

Capturing human knowledge underlying the design and engineering of products has been among the main goals of computational engineering since its very beginning. Over the last decades, various approaches have been proposed to tackle this objective. Among the most promising approaches is the application of graph theory for representing product structures by defining nodes representing entities and edges representing relations among them. The concrete meaning of these structures ranges from geometry representations over hierarchical product breakdowns to functional descriptions and flows of information or resources. On top of these graph structures, graph rewriting techniques provide another powerful layer of technology. By enabling the formal definition of rules for transforming graph structures, they allow on the one hand side to formally capture the engineering development process. On the other hand, the assembly of rewriting rules into graph grammars allows for an exhaustive search of the solution space of the engineering problem at hand. In combination with search strategies, an automated optimization of the design under given constraints and objectives can be realized. The paper provides an overview of the current state-of-the-art in graph rewriting and its applications in engineering design, with a focus on the built environment. It concludes with a discussion of the progress achieved and the missing research gaps.

Digital engineering: expanding the advantage

ABSTRACT Digital transformation – the pervasive incorporation of digital technology into virtually every process and system – is arguably the greatest force of change within the naval engineering community. Digital innovation is disrupting traditional ship design paradigms and giving rise to new ways of modernising and sustaining a future integrated force structure. This paper highlights digital transformation as a core strategic initiative that is aligned with the U.S. Department of Defense Digital Engineering Strategy. Recognising the need to expand the U.S. Navy’s advantage over its competitors, this paper identifies foundational elements required to transform current engineering design and development processes. Next, a multi-factor framework is introduced to align traditional processes employed for physical system design and development with a new digital paradigm in recognition of the highly integrated nature of Model Based Systems Engineering (MBSE). Finally, discussion will focus on efforts underway to leverage advanced computational models and highlight the digital engineering use case for Naval Power and Energy Systems (NPES).

Qualimetry Essentials Applied to Embedded Software Development

ABSTRACTWith the initial goal of filling gaps in the definition, assessment, control, and prediction of automotive embedded software quality, including standards and regulatory compliance constraints, a three‐year research study was conducted. The multiple contributions of the study to theoretical and applied qualimetry have helped to define a theoretical framework for quality control and monitoring of engineering and product development processes. Then, demonstrating the practicality of this solution, this study was applied on a real example from the automotive industry. This framework initially developed in the scope of embedded software is also applicable to systems and embedded systems, and makes these contributions have an impact on all industrial sectors.

Confidence in Flame Impulse Response Estimation From Large Eddy Simulation With Uncertain Thermal Boundary Conditions

Abstract Thermoacoustic stability analysis is an essential part of the engine development process. Typically, thermoacoustic stability is determined by hybrid approaches. These approaches require information on the flame dynamic response. The combined approach of advanced system identification (SI) and large eddy simulation (LES) is an efficient strategy to compute the flame dynamic response to flow perturbation in terms of the finite impulse response (FIR). The identified FIR is uncertain due in part to the aleatoric uncertainties caused by applying SI on systems with combustion noise and partly due to epistemic uncertainties caused by lack of knowledge of operating or boundary conditions. Carrying out traditional uncertainty quantification techniques, such as Monte Carlo, in the framework of LES/SI would be computationally prohibitive. As a result, the present paper proposes a methodology to build a surrogate model in the presence of both aleatoric and epistemic uncertainties. Specifically, we propose a univariate Gaussian Process (GP) surrogate model, where the final trained GP takes into account the uncertainty of SI and the uncertainty in the combustor back plate temperature, which is known to have a considerable impact on the flame dynamics. The GP model is trained on the FIRs obtained from the LES/SI of turbulent premixed swirled combustor at different combustor back plate temperatures. Due to the change in the combustor back plate temperature the flame topology changes, which in turn influences the FIR. The trained GP model is successful in interpolating the FIR with confidence intervals covering the “true” FIR from LES/SI.

Analysis of dynamic characteristics and sensitivity of hydrogen-oxygen expansion cycle rocket engine system

The success of the launch mission depends on the dynamic characteristics of the rocket engine system, while the engine development process is based on the parameter sensitivity analysis. However, the dynamic characteristics and parameter sensitivity of the hydrogen-oxygen expansion cycle engine remain unclear. This research built the simulation model of basic components and overall system of the hydrogen-oxygen expansion cycle engine. A 3-factor and 9-level numerical simulation study was carried out based on the structural parameters of the cooling channel. Results show that at 0.1s after the ignition of the engine, the speed of oxygen pump drops by 16.4%, while the torque of the hydrogen turbine drops by 43.6%. The rise of coolant temperature between the inlet of the cooling channel and the outlet of combustion chamber is about 185 K, which is about 4 times of that between the outlet of combustion chamber and the first section outlet of the nozzle. The sensitivity of the response time to the rib height reaches 0.36, while the sensitivity of response time to the rib width and the nozzle wall thickness are 0.15 and 0.12, respectively. These findings contribute to the start-up analysis and design of the hydrogen-oxygen expansion cycle engine.

Information integration and instruction authoring of augmented assembly systems

Augmented assembly (AA) is being gradually incorporated into manual assembly owing to its abundant instruction forms, high efficiency of information transmission, and robust interactivity. However, a lack of a unified description model for assembly information and irregular instruction design forms leads to difficulties in instruction authoring and generation, inconveniences for data management, and low system portability. To address these issues, this paper presents an information-integration and instruction-authoring method for AA systems. First, design guidelines for the AA instructions are established with the aim of minimizing the user's cognitive load. After that, the designing of visual elements is performed based on the design guidelines, and the information model of the assembly information and instructions is built using Unified Modeling Language. Based on Extensible Markup Language files and Unity3D engine, a standard and rapid development process is presented for deploying the AA system to Hololens2 devices. The usability and replicability of the designed system are demonstrated, and a user study is carried out. The user's task performance is evaluated using completion time and errors as metrics. The NASA-task load index scale is used to estimate the user's workload, and the Likert scale reflects the user's subjective perception of the system and instructions. The results show that the proposed AA instructions can effectively improve the user's task performance; reduce their workload, especially the cognitive load; and improve their assembly experience.

ИССЛЕДОВАНИЕ ДВИЖЕНИЯ СЫПУЧИХ МАТЕРИАЛОВ В ВИНТОВЫХ СИТАХ

The work purpose is to increase the productivity of bulk material separation by means of engineering process development based on fundamentally new engineering equipment in the form of spiral sieves, the novelty of which is confirmed by six patents for invention of the Russian Federation. In the work there was used a complex method of investigations. 
 Analytical methods allowed offering dependences for the definition of bulk material longitudinal motion speed in spiral sieves. Experimental investigations were carried out in order to confirm analytical dependences. The analytical investigation of bulk material separation into fractions for the purpose of conditional model choice for its description is presented. A mathematical model choice is fulfilled. There is analyzed a model of continuous medium and that of a material particle. A mathematical model is developed to determine a speed of longitudinal motion of bulk material from charging to unloading. There is presented not only a circuit and an experimental plant created in metal version, but the results of experimental investigations of bulk medium motion parameters subject to spiral sieve design peculiarities are shown which presented a coincidence level high enough.

Cylinder Pressure Prediction of An HCCI Engine Using Deep Learning

Engine tests are both costly and time consuming in developing a new internal combustion engine. Therefore, it is of great importance to predict engine characteristics with high accuracy using artificial intelligence. Thus, it is possible to reduce engine testing costs and speed up the engine development process. Deep Learning is an effective artificial intelligence method that shows high performance in many research areas through its ability to learn high-level hidden features in data samples. The present paper describes a method to predict the cylinder pressure of a Homogeneous Charge Compression Ignition (HCCI) engine for various excess air coefficients by using Deep Neural Network, which is one of the Deep Learning methods and is based on the Artificial Neural Network (ANN). The Deep Learning results were compared with the ANN and experimental results. The results show that the difference between experimental and the Deep Neural Network (DNN) results were less than 1%. The best results were obtained by Deep Learning method. The cylinder pressure was predicted with a maximum accuracy of 97.83% of the experimental value by using ANN. On the other hand, the accuracy value was increased up to 99.84% using DNN. These results show that the DNN method can be used effectively to predict cylinder pressures of internal combustion engines.

Design of a virtual test cell based on GMDH-type neural network for a heavy-duty diesel engine

The engine development process faces big challenges from new strict emission regulations in addition to the need for fuel efficiency improvements. The Software-in-the-Loop (SiL) and Hardware-in-the-Loop (HiL) environments decreases the required time during engine development, calibration, verification, and validation of the product. An accurate and easy to build dyno-engine model with real-time operational ability is required for this purpose. Artificial Neural Networks (ANN) have shown ability to model dynamic and complex systems like internal combustion engines. In this paper, the Group Method of Data Handling (GMDH) algorithm was utilized to build an ANN model of a heavy-duty diesel engine. One objective is to reduce the amount of manual labor on the results during the ANN model development process. The GMDH algorithm is a self-organizing process that will find the system laws and optimize the model structure automatically in one iteration. The GMDH model results were compared with a model developed by Levenberg-Marquardt Backpropagation (LM-BP) algorithm. The ANN models used actuator signals from an Engine Management System (EMS) to simulate the engine operation parameters. As revealed by the simulation results, the ANN models successfully predicted engine torque, fuel flow, and NOx concentration. The GMDH model as a self-organized model reduced lead time, had slightly higher transient cycle accuracy, had fewer inconsistent predictions, and demonstrated better extrapolation capability. The prediction accuracy for transient operation was improved by shifting the predicted value by calculating time delay and a decrease of 76.66% for fuel flow and 66.51% for NOX concentration in model accuracy were achieved. The GMDH dyno-engine model can be effectively applied as a virtual test cell instrument for testing, calibration, and optimization purposes.

Knock detection in a quasi-dimensional SI combustion simulation using ignition delay and knock combustion modeling

In spark ignition (SI) engines, knock suppression is essential to improve fuel economy. Integrating new technologies into already complex downsized turbocharged engines increases the number of design and control variables substantially and requires extensive engine testing. Utilizing simulation-based study in an engine development process is crucial to reduce expensive and time-consuming engine tests. A quasi-dimensional (quasi-D) two-zone SI engine model is typically used in SI engine simulations. However, the usefulness of quasi-D-based simulation tools is often limited by the predictive capability of knock models. In this study, a novel knock model intended to be implemented in quasi-D SI engine simulation was developed. The model comprises a two-stage ignition delay model, a knock combustion model, and a knock index model. The knock model simulates the heat release spike during a knock combustion, which can be observed from the apparent heat release rate generated with the low-pass filtered cylinder pressure data. The model was calibrated and validated against engine experimental data. Its capability of knock detection and knock-limited spark timing estimation was demonstrated under various conditions of octane numbers, air–fuel equivalence ratios, and coolant temperatures with toluene primary reference fuel (TRPF). The knock model was also able to capture different knock characteristics between TPRF and primary reference fuel (PRF) in modern downsized turbocharged SI engines. The proposed methodology represents a useful tool to be employed during the development phase of an engine to reduce the experimental efforts while improving the engine performance at knock borderline.

A predictive combustion model for one-dimensional gasoline engine simulation

A new predictive combustion model for a one-dimensional computational fluid dynamics tool in the multibody dynamics processes of gasoline engines was developed and validated. The model consists of (1) a turbulent burning velocity model featuring a flame radius–based transitional function, steady burning velocity that considers local quenching using the Karlovitz number and laminarization by turbulent Reynolds number, as well as turbulent flame thickness and its quenching model near the liner wall, and (2) a knock model featuring auto-ignition by the Livengood–Wu integration and ignition delay time obtained using a full-kinetic model. The proposed model and previous models were verified under a wide range of operating conditions using engines with widely different specifications. Good agreement was only obtained for combustion characteristics by the proposed model without requiring individual calibration of model constants. The model was also evaluated for utilization after prototyping. Improved accuracy, especially of ignition timing, was obtained after further calibration using a small amount of engine data. It was confirmed that the proposed model is highly accurate at the early stage of the engine development process, and is also applicable for engine calibration models that require higher accuracy.

Cyber Security in IoT communication (Internet of Things) on Smart Home

The Internet of Things (IoT) that are currently applied with the combination of smart devices that connect with each other devices over the Internet from smartphone to other household devices that are assembled in a smart home-based concept. Smart Home is one of the concepts of implementing IoT technology, which is the implementation of Software Engineering. However, in document requirements in its engineering process development, often the requirements for cyber security aspect is neglected because it is considered as a secondary requirement. Therefore, it will be done analysis process requirements on the system by specializing in the cyber security aspect. In this paper, it will be analyzed about cyber security requirements of smart home IoT communication using methodology of Security Quality Requirements Engineering (SQUARE). The methodology of cyber security requirements analysis use SQUARE methodology consisting of 9 stages consist of agreement, identification, development, and analysis. The identification and analysis that has been done also has resulted in security requirement along with the implementation required for a secure smart home system. The analysis result consists of four types of requirements such as Elicit Security Requirement, Categorize Requirement, Prioritize Requirement, and Requirement Inspection. It is very helpful in analyzing while providing recommendations to the security requirements of the system which are used to keep the availibility and continuity of the software as well as the integrity of the smart home systems that are being developed.